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Structural and Functional Modeling of Artificial Bioactive Proteins

Štambuk, Nikola; Konjevoda, Paško (2017) Structural and Functional Modeling of Artificial Bioactive Proteins. Information, 8 (1). ISSN 2078-2489

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A total of 32 synthetic proteins designed by Michael Hecht and co-workers was investigated using standard bioinformatics tools for the structure and function modeling. The dataset consisted of 15 artificial α-proteins (Hecht_α) designed to fold into 102-residue four-helix bundles and 17 artificial six-stranded β-sheet proteins (Hecht_β). We compared the experimentally-determined properties of the sequences investigated with the results of computational methods for protein structure and bioactivity prediction. The conclusion reached is that the dataset of Michael Hecht and co- workers could be successfully used both to test current methods and to develop new ones for the characterization of artificially-designed molecules based on the specific binary patterns of amino acid polarity. The comparative investigations of the bioinformatics methods on the datasets of both de novo proteins and natural ones may lead to: (1) improvement of the existing tools for protein structure and function analysis ; (2) new algorithms for the construction of de novo protein subsets ; and (3) additional information on the complex natural sequence space and its relation to the individual subspaces of de novo sequences. Additional investigations on different and varied datasets are needed to confirm the general applicability of this concept.

Item Type: Article
Uncontrolled Keywords: synthetic protein ; structure prediction ; function prediction ; de novo design
Subjects: BIOMEDICINE AND HEALTHCARE > Basic Medical Sciences
SOCIAL SCIENCES > Information and Communication Sciences
Divisions: Division of Molecular Medicine
NMR Center
Project titleProject leaderProject codeProject type
Modeliranje bioaktivnih molekula i ispitivanje njihovih svojstava i učinka-Nikola Štambuk098-0982929-2524MZOS
Depositing User: Nikola Štambuk
Date Deposited: 13 Jun 2019 12:31
DOI: 10.3390/info8010029

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